Method of Using Human Physiological Responses as Inputs to Hydrocarbon Management Decisions

ABSTRACT

A method of analyzing hydrocarbon-related data is disclosed. Data representative of a hydrocarbon entity is presented. A physiological response of a viewer of the data is sensed. The physiological response is associated with the data. The data and a representation of the associated physiological response is outputted.

CROSS REFERENCE TO RELATED APPLICATIONS

This Application is a continuation of U.S. patent application Ser. No.13/376,810 filed Dec. 7, 2011, entitled METHOD OF USING HUMANPHYSIOLOGICAL RESPONSES AS INPUTS TO HYDROCARBON MANAGEMENT DECISIONS,which was a national stage entry under 35 U.S.C. 371 fromPCT/US2010/034563, filed May 12, 2010, entitled METHOD OF USING HUMANPHYSIOLOGICAL RESPONSES AS INPUTS TO HYDROCARBON MANAGEMENT DECISIONS,which claimed the benefit of U.S. Provisional Application 61/238,945,filed Sep. 1, 2009, entitled METHOD OF USING PHYSIOLOGICAL RESPONSES ASINPUTS TO HYDROCARBON MANAGEMENT DECISIONS. U.S. patent application Ser.No. 13/376,810 and 61/238,945 and international patent applicationPCT/US2010/034563 are hereby incorporated by reference in theirentirety.

TECHNICAL FIELD

Disclosed aspects relate to managing hydrocarbon resources, and morespecifically, to using human physiological response as an input todecision-making in identifying and managing hydrocarbon resources.

BACKGROUND OF THE DISCLOSURE

This section is intended to introduce various aspects of the art, whichmay be associated with aspects of the disclosed techniques andmethodologies. This discussion is believed to assist in providing aframework to facilitate a better understanding of particular aspects ofthe disclosure. Accordingly, this section should be read in this lightand not necessarily as an admission of prior art.

In the hydrocarbon industry computer-based or computer-assistedinterpretation and decisions are made daily. The interpretation anddecisions have associated uncertainty which may not be capturedaccurately. Attempts to describe the quality and level of certainty(QLOC) associated with these activities to date have focused on eitheruncertainty associated with data and/or qualitativepost-analysis/comments assigned to these data, objects or decisions.Numerous methods are available to represent data uncertainty. Thesecomments, often referred to as metadata, may describe the QLOC for theentire object and may incorporate geologic and data issues. In thisprocess, the human factors associated with interim decisions, poor data,geologic complexity, user bias or lack of experience can be overlookedor not recorded. As a result final decisions may be based oninsufficient or erroneous information, resulting in a sub-optimalunderstanding of the QLOC. There have been efforts to have usersdocument interim issues in a digital journal/diary. This has been foundto provide insufficient or erroneous information because user-suppliedcomments are captured sporadically at best and are subject to user bias,knowledge, and/or experience. Additionally, the comments frequently donot address negativity or lack of confidence in the decision.Furthermore, the comments are not spatially or temporally captured withthe object, data or workflow being analyzed. Additionally, thiscommenting process is time-intensive and therefore is done infrequently,and even when done properly the commenting process increases the time tocomplete a data evaluation. There is a need in the hydrocarbon industryfor time-efficient processes to capture continuous human factorsassociated with computer based oil and gas interpretation and decisionsto improve the quality and level of certainty and understanding withinthe industry resulting in improved hydrocarbon management.

SUMMARY

In one aspect, a method of analyzing hydrocarbon-related data isprovided. Data representative of a hydrocarbon entity is presented. Aphysiological response of a viewer of the data is sensed. Thephysiological response is associated with the data. The data and arepresentation of the associated physiological response is outputted.

According to methodologies and techniques disclosed herein, presentingthe data may include displaying the data. The data may be displayed in agraphical form. The representation of the associated physiologicalresponse may be displayed in a graphical form, and may be superimposedupon the data. The physiological response may include one or more of:brainwave activity, movement of an eye, position of an eye, gaze, musclemovement, body temperature, heart rate, pulmonary performance, change intone of voice, a rate of use of an input device, and a position of aninput device relative to the presented data representative of thehydrocarbon entity. Outputting the data and the associatedrepresentation of the physiological response may include storing thedata and the representation in a memory, or displaying the data and agraphical representation of the physiological response. Thephysiological response may be interpreted based on information regardingthe viewer. Outputting the data may include storing the data in a rawform or a processed form.

In another aspect, an apparatus for analyzing hydrocarbon-related datais provided. One or more sensors measure physiological responses of auser viewing hydrocarbon-related data. A processor determines a natureof the physiological response and associates the physiological responsewith the hydrocarbon-related data responsible therefore. An outputmechanism stores information describing the physiological response withthe hydrocarbon-related data responsible therefor.

According to methodologies and techniques disclosed herein, theapparatus may further include a display for viewing thehydrocarbon-related data. The output mechanism may be a display or adata storage mechanism. The sensors may include a device that recordsbrainwave activity of the user. The sensors may include an eye-trackingdevice that senses one or more of eye movement of the user, eye positionof the user, and gaze of the user. The eye-tracking device may bemounted on the display. The sensors may sense use of an input device,such as a computer mouse, a computer trackball, or a computer keyboard,as it is manipulated by the user.

In another aspect, a method of hydrocarbon management is provided.Hydrocarbon-related information is obtained. The hydrocarbon-relatedinformation is viewed. A physiological response is sensed while thehydrocarbon-related information is being viewed. A representation of thephysiological response is presented. Hydrocarbons are managed based onthe physiological response.

According to methodologies and techniques described herein, therepresentation of the physiological response may be presentedconcurrently with a display of the hydrocarbon-related information.Certainty data related to the hydrocarbon-related information may beobtained, and the certainty data may be presented concurrently with therepresentation of the physiological response and the display of thehydrocarbon-related information, so that hydrocarbons may be managedbased on the certainty data and the physiological response. Sensing aphysiological response may include sensing brainwave activity of a userwhile the user is viewing the hydrocarbon-related information. Sensing aphysiological response may include tracking an eye of a user while theuser is viewing the hydrocarbon-related information, to determine atleast one of eye movement, eye position, and gaze.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other advantages may become apparent upon reviewingthe following detailed description and drawings of non-limiting examplesof embodiments.

FIG. 1 is a perspective view of a device for measuring brainwaveactivity.

FIG. 2 is a perspective view of a device for measuring eye movement.

FIG. 3 is a seismic section overlaid with visualization of eye tracking.

FIG. 4 is a block diagram of a system using human physiological responseinformation. This system could consist of 1 or more human physiologicalresponse (HPR) monitoring devices.

FIG. 5 is a side elevational view of a two-dimensional seismic sectionshowing primary reflectors along with 2 wells.

FIG. 6 is a side elevational view of the two-dimensional seismic sectionof FIG. 5 as interpreted by a geoscientist.

FIG. 7 is a side elevational view of the two-dimensional seismic sectionof FIG. 5 as interpreted by a non-geoscientist.

FIG. 8 is a map view of a geologic dataset with confidence levels,derived from HPR inputs, graphically displayed thereon.

FIG. 9 is a map view of the geologic dataset of FIG. 8 with datauncertainty graphically displayed thereon.

FIG. 10 is a map view of the geologic dataset of FIG. 8 with eyetracking results, derived from HPR inputs, graphically displayedthereon.

FIG. 11 is a map view of the geologic dataset of FIG. 8, with theinformation of FIGS. 8 and 9 also displayed thereon.

FIG. 12 is a map view of the geologic dataset of FIG. 11 with structuralcontours displayed over the HPR information.

FIG. 13 is a flowchart of a method using HPR techniques in a hydrocarbonmanagement decision workflow.

FIG. 14 is a flowchart of a multi-user method using HPR techniques in ahydrocarbon management decision workflow.

FIG. 15 is a flowchart of a method using HPR techniques in a hydrocarbonmanagement decision workflow according to another aspect.

FIG. 16 is a block diagram of a computer system according to aspects ofthe disclosed methodologies and techniques.

FIG. 17 is a flowchart of a method according to aspects of the disclosedmethodologies and techniques.

FIG. 18 is a side elevational view of a subsurface region.

FIG. 19 is a flowchart of a method according to aspects of the disclosedmethodologies and techniques.

To the extent the following detailed description is specific to aparticular embodiment or a particular use of the disclosed techniques,this is intended to be illustrative only and not to be construed aslimiting the scope of the invention. On the contrary, it is intended tocover all alternatives, modifications and equivalents that may beincluded within the spirit and scope of the invention, as defined by theappended claims.

DETAILED DESCRIPTION

Some portions of the detailed description which follows are presented interms of procedures, steps, logic blocks, processing and other symbolicrepresentations of operations on data bits within a memory in acomputing system or a computing device. These descriptions andrepresentations are the means used by those skilled in the dataprocessing and analysis arts to most effectively convey the substance oftheir work to others skilled in the art. In this detailed description, aprocedure, step, logic block, process, or the like, is conceived to be aself-consistent sequence of steps or instructions leading to a desiredresult. The steps are those requiring physical manipulations of physicalquantities. Usually, although not necessarily, these quantities take theform of electrical, magnetic, or optical signals capable of beingstored, transferred, combined, compared, and otherwise manipulated. Ithas proven convenient at times, principally for reasons of common usage,to refer to these signals as bits, values, elements, symbols,characters, terms, numbers, or the like.

Unless specifically stated otherwise as apparent from the followingdiscussions, terms such as “presenting”, “sensing”, “associating with”,“outputting”, “displaying”, “superimposing”, “storing”, “interpreting”,“obtaining”, “viewing”, “managing”, “determining”, “measuring”,“recording”, and “tracking”, or the like, may refer to the action andprocesses of a computer system, or other electronic device, thattransforms data represented as physical (electronic, magnetic, oroptical) quantities within some electrical device's storage into otherdata similarly represented as physical quantities within the storage, orin transmission or display devices. These and similar terms are to beassociated with the appropriate physical quantities and are merelyconvenient labels applied to these quantities.

Embodiments disclosed herein also relate to an apparatus for performingthe operations herein. This apparatus may be specially constructed forthe required purposes, or it may comprise a general-purpose computerselectively activated or reconfigured by a computer program or codestored in the computer. Such a computer program or code may be stored orencoded in a computer readable medium or implemented over some type oftransmission medium. A computer-readable medium includes any medium ormechanism for storing or transmitting information in a form readable bya machine, such as a computer (‘machine’ and ‘computer’ are usedsynonymously herein). As a non-limiting example, a computer-readablemedium may include a computer-readable storage medium (e.g., read onlymemory (“ROM”), random access memory (“RAM”), magnetic disk storagemedia, optical storage media, flash memory devices, etc.). Atransmission medium may be twisted wire pairs, coaxial cable, opticalfiber, or some other suitable transmission medium, for transmittingsignals such as electrical, optical, acoustical or other form ofpropagated signals (e.g., carrier waves, infrared signals, digitalsignals, etc.).

Furthermore, modules, features, attributes, methodologies, and otheraspects can be implemented as software, hardware, firmware or anycombination thereof. Wherever a component of the invention isimplemented as software, the component can be implemented as astandalone program, as part of a larger program, as a plurality ofseparate programs, as a statically or dynamically linked library, as akernel loadable module, as a device driver, and/or in every and anyother way known now or in the future to those in the art of computerprogramming. Additionally, the invention is not limited toimplementation in any specific operating system or environment.

Various terms as used herein are defined below. To the extent a termused in a claim is not defined below, it should be given the broadestpossible definition persons in the pertinent art have given that term asreflected in at least one printed publication or issued patent.

As used herein, “and/or” placed between a first entity and a secondentity means one of (1) the first entity, (2) the second entity, and (3)the first entity and the second entity. Multiple elements listed with“and/or” should be construed in the same fashion, i.e., “one or more” ofthe elements so conjoined.

As used herein, “computer algorithm” is a set of logical commands that acomputer executes.

As used herein, “computer program” is a process that runs inside of thevolatile memory of a computer. Computer programs have algorithmic logicand data stored in a binary format. As used in the discussion herein, acomputer program does not exist when the computer is dormant and not yetloaded into the volatile memory of a computer. For example, a wordprocessor exists initially on a computer's hard drive as a computerapplication. When a computer user double-clicks on an on-screen iconrepresenting the word processor, a new computer program is started bycompiling and/or executing the computer application associatedtherewith. When the user exits the word processor the computer programends. A user can open the word processor twice at the same time, andthis would constitute two different running computer programs becauseeach would have its own data and volatile memory assigned thereto. Forthe purpose of describing aspects of the disclosed techniques, acomputer program only exists if all or part of it is executing currentlyin a computer's volatile memory.

As used herein, “decision-making process” may include one or more of theacts of using a computer to visualize or display information or data,analyzing or interpreting the data or information, and concluding upon apresent or future course of action based on the analysis orinterpretation.

As used herein, “displaying” includes a direct act that causesdisplaying, as well as any indirect act that facilitates displaying.Indirect acts include providing software to an end user, maintaining awebsite through which a user is enabled to affect a display,hyperlinking to such a website, or cooperating or partnering with anentity who performs such direct or indirect acts. Thus, a first partymay operate alone or in cooperation with a third party vendor to enablethe reference signal to be generated on a display device. The displaydevice may include any device suitable for displaying the referenceimage, such as without limitation a CRT monitor, a LCD monitor, a plasmadevice, a flat panel device, or printer. The display device may includea device which has been calibrated through the use of any conventionalsoftware intended to be used in evaluating, correcting, and/or improvingdisplay results (e.g., a color monitor that has been adjusted usingmonitor calibration software). Rather than (or in addition to)displaying the reference image on a display device, a method, consistentwith the invention, may include providing a reference image to asubject. “Providing a reference image” may include creating ordistributing the reference image to the subject by physical, telephonic,or electronic delivery, providing access over a network to thereference, or creating or distributing software to the subjectconfigured to run on the subject's workstation or computer including thereference image. In one example, the providing of the reference imagecould involve enabling the subject to obtain the reference image in hardcopy form via a printer. For example, information, software, and/orinstructions could be transmitted (e.g., electronically or physicallyvia a data storage device or hard copy) and/or otherwise made available(e.g., via a network) in order to facilitate the subject using a printerto print a hard copy form of reference image. In such an example, theprinter may be a printer which has been calibrated through the use ofany conventional software intended to be used in evaluating, correcting,and/or improving printing results (e.g., a color printer that has beenadjusted using color correction software).

As used herein, “graphical form” refers to any visual rendering orrepresentation of information or data, such as text or numericalrendering, pictorial rendering, symbology, and the like.

As used herein, “hydrocarbon reservoir” is a reservoir containing anyhydrocarbon substance, including for example one or more than one of anyof the following: oil (often referred to as petroleum), natural gas, gascondensate, tar and bitumen.

As used herein, “machine-readable medium” refers to a medium thatparticipates in directly or indirectly providing signals, instructionsand/or data. A machine-readable medium may take forms, including, butnot limited to, non-volatile media (e.g. ROM, disk) and volatile media(RAM). Common forms of a machine-readable medium include, but are notlimited to, a floppy disk, a flexible disk, a hard disk, a magnetictape, other magnetic medium, a CD-ROM, other optical medium, punchcards, paper tape, other physical medium with patterns of holes, a RAM,a ROM, an EPROM, a FLASH-EPROM, or other memory chip or card, a memorystick, and other media from which a computer, a processor or otherelectronic device can read.

As used herein, “subsurface” means beneath the top surface of any massof land at any elevation or over a range of elevations, whether above,below or at sea level, and/or beneath the floor surface of any mass ofwater, whether above, below or at sea level.

As used herein, a “hydrocarbon entity” is any object or workflowrelating to hydrocarbon management, and any computer-basedinterpretation of such an object or workflow. Example objects mayinclude: geologic objects or concepts such as horizons, faults, andintrusive events; stratigraphic features such as unconformities,downlap, offlap, and the like; well trajectories, well casing plans,completion intervals, and hydrocarbon contacts. Other objects mayinclude geologic models, reservoir models, geobodies etc. Workflows mayinclude seismic interpretation, data reconnaissance, well planning,field surveillance, reservoir simulation history matching, geologicinterpretation, connectivity analysis etc.

As used herein, “hyrdrocarbon management” includes hydrocarbonextraction/production, hydrocarbon exploration, identifying potentialhydrocarbon resources, identifying well locations, determining wellinjection and/or extraction rates, identifying reservoir connectivity,acquiring, disposing of and/or abandoning hydrocarbon resources,reviewing prior hydrocarbon management decisions, and any otherhydrocarbon-related acts or activities.

As used herein, “gaze” refers to a length of time a user looks at adisplayed object or dataset, or at a portion thereof.

Example methods may be better appreciated with reference to flowdiagrams. While for purposes of simplicity of explanation, theillustrated methodologies are shown and described as a series of blocks,it is to be appreciated that the methodologies are not limited by theorder of the blocks, as some blocks can occur in different orders and/orconcurrently with other blocks from that shown and described. Moreover,less than all the illustrated blocks may be required to implement anexample methodology. Blocks may be combined or separated into multiplecomponents. Furthermore, additional and/or alternative methodologies canemploy additional blocks not shown herein. While the figures illustratevarious actions occurring serially, it is to be appreciated that variousactions could occur in series, substantially in parallel, and/or atsubstantially different points in time.

Human physiological response (HPR) technology is an emerging technologythat has been used in the computer gaming industry, the medical field,and the military to permit a user to interact with a computer. HPRtechnology as currently deployed, however, uses only a single type ofHPR technology in any given application. For example, weapons systemsmay use an eye-tracking mechanism to identify potential targets. Acomputer gaming system may detect other physiological responses, such asbrainwaves of a computer user, to actively effectuate predeterminedinstructions or actions in an executing a computer program. According toaspects of the disclosed techniques and methodologies, one or moreevidences of human physiological response (HPR) and mechanicalattributes are assigned passively and in real-time tohydrocarbon-related data, interpretation of said data, and/or indecision-based hydrocarbon-related workflows. The measurements obtainedfrom one or more HPR sensors may be stored as raw data or as processeddata associated with the hydrocarbon-related data, and provide acharacterization of the mental state of a viewer of thehydrocarbon-related data.

Types of HPR modalities envisioned include human brainwave responses asdetected through electroencephalography (EEG), eye tracking, muscletracking, cursor movement speeds, digitization rates and the like.Although devices are available to monitor and record single HPRmodalities, aspects disclosed herein may combine multiple devices (andmodalities) to analyze a given data set. An example of an inexpensivedevice that monitors a viewer's physiological responses is shown inFIG. 1. Device 10 uses EEG technology and the detection of movement offacial and/or scalp muscles to interpret a viewer's mental state and/oremotion. Device 10 may be a brainwave monitoring headset known as EPOC,supplied by Emotiv Systems of San Francisco, Calif. Conventionally,device 10 may be used to facilitate active human-computer interactionsin video/computer games and other computer software. According todisclosed aspects, human physiological responses—such as brain waveactivity—are used to passively evaluate, interpret, and otherwise assistmaking decisions relating to hydrocarbon management. The measurementsmay be associated with a single input point/event belonging to ahydrocarbon entity. Alternatively, the measurements may be analyzed andassigned to a group of points (subset or local region/area) belonging toa hydrocarbon entity, or may be associated with (or summarized for) theentire hydrocarbon entity. Quality and level of certainty (QLOC)measurements may be visualized to focus a viewer's attention toanomalies in the data, and for various types of data processingactivities such as compression, classification, and the like.

Another method of measuring human physiological response is aneye-tracking mechanism, which is shown at reference number 20 in FIG. 2.Eye-tracking mechanism 20 is shown as mounted on a display 22 that isdisplaying data to be analyzed by a viewer. An alternative eye-trackingmechanism may be mounted on a helmet or other headgear worn by theviewer. The eye-tracking mechanism as discussed herein includes anassociated computer program that measures eye movement and position, andcan be used to determine precisely what a user is looking at or focusingon. Eye-tracking data obtained by eye-tracking mechanism 20 can berecorded in real-time during a viewer's analysis of displayed data ondisplay 22. The eye-tracking data can be processed and, as shown in FIG.3 at reference number 24, superimposed on the data (in this case seismicdata 25) that is displayed on display 22. The processing of eye-trackingdata may vary from a simple summing of eye-tracking events to a morecomplex process that would involve automated identification of dataregions where anomalous eye-tracking activity is detected.

Still another method of measuring human physiological response isthrough the tracking of muscle movement and/or other physiologicalmechanical activities the user performs while interacting with thecomputer. One example of this is merely noting the keystrokes or mouseclicks performed by a user while evaluating a displayed geologic dataset. For example, the rate at which a user clicks a mouse whileevaluating a data set may be related to the amount of time the user isfocusing on a particular displayed data set. A low mouse click ratesuggests more time is being taken to evaluate the data set, while a highmouse click rate suggests less time is being taken to evaluate the dataset. The mouse click rate may be compared against an average mouse clickrate of the specific user evaluating the data set to determine whetherthe time the specific user is taking to view a data set is greater orless than normal for that user. Another method of measuring mechanicalHPR input may include tracking actual cursor position.

In addition to brainwaves, eye tracking and mechanical computerinteractions, other HPR modalities that may be measured and recordedare: non-brain-related electrical signals, such as heart rate; externalor internal body temperature changes, which may indicate stress orexcitement; and pulmonary performance, such as breathing rate orbreathing depth.

It is to be understood that any apparatus, system, or device formeasuring human physiological response may include a hardware component(such as device 10 or eye-tracking mechanism 20) as well as a computersoftware component that processes signals from its respective hardwarecomponent, as will be further described below.

The HPR modalities disclosed herein may be used separately or incombination. FIG. 4 shows a simplified diagram of a system 30 usingmultiple HPR modalities according to aspects of the disclosedmethodologies and techniques. System 30 includes a device 32 to measurebrainwave activity and facial/scalp muscle movement. Device 32 may besimilar to device 10 in FIG. 1, which uses EEG technology or other meansto measure brainwave activity and facial/scalp muscle movement. System30 also includes an eye-tracking mechanism 33 that determines what auser is looking at or focusing on. Eye-tracking mechanism 33 may besimilar to eye-tracking mechanism 20. A microphone 34 may be used torecord oral commentary as well as to sense stress levels detectable inthe user's voice. A mouse 35 a and/or keyboard 35 b provides mechanicalinput as previously described. Other HPR sensors 36, such as heart rate,temperature, blood pressure, may be part of system 30. The device 32,eye-tracking mechanism 33, microphone 34, mouse and/or keyboard 35 a, 35b, and other HPR sensors send signals to a processor 37 in response to auser viewing a visual representation of a dataset on a display 38. Theeye-tracking mechanism determines which portion of the displayed dataset is being focused on by the user. Device 32 senses brainwave activityand/or facial muscle movement, and the other HPR sensors record theuser's reaction to the focused-on portion of the displayed dataset. Anycomputer software component of an HPR apparatus, system, or device maybe run on processor 37. The processor includes further capability,through additional computer software installed thereon, to analyze thesensed reaction of the user for a given portion of the displayeddataset. For example, brain wave activity indicating a confused orunsure mental state suggests that whatever is being looked at or focusedon by the user may need further review. Brain wave activity indicating ahappy or excited state may suggest that whatever is being looked at orfocused on indicates positive results and/or certainty in the dataset.The system may modify the displayed dataset by graphically or visuallyhighlighting or outlining the focused-on regions. The system may storethe modified dataset in a memory or other data storage device 39.Alternatively, the sensed HPR information may be stored in a raw orunprocessed state for further analysis, examples of which may bedescribed below.

The use of HPR technologies may be used with other data uncertaintymeasures as well as incorporating information regarding the viewer.Recording viewer information aids in correctly interpreting thesignificance of the HPR responses. FIGS. 5-7 depict an example of howrecording viewer information aids such a correct interpretation. Anexample is the task of creating a seismic interpretation between twowells to determine whether an infill well is required to be drilled.FIG. 5 depicts a two-dimensional seismic section 40 showing primaryfeatures that have reflected the seismic signals, such as a fault 42 anda stratigraphic boundary 44, along with two wells 46, 48. Blackrectangles 50, 52, 54 represent completion intervals where the wellshave encountered hydrocarbons. Uncertainty associated with the seismicdata is shown by three distinct shades of gray 56 a, 56 b, 56 c. Whenthe seismic section is viewed by a geoscientist, the geologic andgeophysical and reservoir experience of the geoscientist providesvaluable contextual information on how to interpret the seismic data. Asshown in FIG. 6, solid lines 58 a, 58 b superimposed on the seismic datarepresent high confidence in certain geologic formations, andsuperimposed dashed lines 60 a, 60 b represent low confidence in othergeologic formations. In contrast, a non-geoscientist viewing the seismicdata will form different conclusions, as shown in FIG. 7 by superimposedhigh-confidence lines 58 c, 58 d and low confidence lines 60 c, 60 d. Inparticular, comparing the confidence levels shows the geoscientist haslow confidence about the geologic structure around well 48 (FIG. 6)while the non-geoscientist has high confidence about the same features(FIG. 7). This high confidence is attributed to the non-geoscientist'slack of geologic and engineering experience. For this example, thegeoscientist's interpretation is correct. The lack of confidence of thegeoscientist highlights areas of difficult interpretation due to poordata quality, complex geology, and reservoir information. The HPRinformation displayed by the geoscientist's interpretation may bevaluable information for future work and may help identify areas thatare more uncertain and may require additional review.

The example shown in FIGS. 5-7 demonstrates that thesignificance/meaning of HPR events can be further enhanced byincorporating the experience and knowledge of a viewer of a dataset.User information may be stored in a user profile and accessed wheneverthe user is reviewing datasets. A user profile may contain informationsuch as years of service, areas of expertise (geology, geophysics,reservoir engineering, etc.), work experience (exploration, development,production), geologic experience (elastics, deep water, carbonates,overthrust etc.), engineering experience (drilling, simulation,operations, etc.), and other information relevant to analyzing datasets. Incorporating the user information into dataset analysis mayprovide additional context as to the mental state of a viewer of adataset. The user profile can be either entered manually into a systemthat manages the HPR, or the user profile can be obtained from a user'scomputer login name. The user profile can then be modified manually bythe user. Alternatively, the user profile may be modified withstatistics from previous HPR responses stored in the HPR managementsystem. For example, the user profile may be automatically re-evaluatedbased on the user's HPR responses, or even based on other users' HPRresponses.

Aspects described herein increase the overall understanding of thecertainty associated with interpretation and decision-making workflowsin hydrocarbon management, improve the quality of interpretation, andreduce time to adopt new interpretation scenarios by identifying areaswhich could have multiple options or low QLOC. The potential businessimpact is improved reservoir management and ultimately increasedprofits.

Aspects of the disclosed methodologies and techniques may aid inhydrocarbon management in many ways. For example, a user may interpretsubterranean or subsurface geologic features of interest using amulti-modality system as shown in FIG. 1 or FIG. 4. The user activatesthe HPR system and begins the subsurface seismic interpretation process.The HPR system begins recording, noting the user's name. While the useris interpreting a subterranean surface the HPR system records and storesthe HPR signals, and associates the HPR signals with the subterraneansurface and/or each of the surface's individual components (seismic,horizons, faults, wells etc) as displayed on a monitor. The HPR signalsmay be associated with data elements of any size (for example, points,lines, sets of points, geometric/geographic objects, surfaces, volumes,entire dataset). The HPR data may be visualized during theinterpretation process or after the initial interpretation is completed.HPR data may be incorporated with information regarding data uncertaintyto further develop a more holistic understanding of uncertaintiesinvolved in the interpretation activity. HPR information may helpidentify the presence of subtle features (such as small faults,stratigraphy, hydrocarbon indicators, etc.) while interpreting byshowing areas on the interpreted surface where, even though the featurewasn't interpreted because the user was thinking about the featurepossibly existing, it would be identified by HPR inputs and shown on thefinal interpretation. This type of analysis and visualization couldoccur either during or after the interpretation of the surface.

Another post-interpretation use of HPR is to assess the quality of aHPR-assisted interpretation. In this example, combining the HPRmodalities with conventional data uncertainty techniques could provideinsights into the level of certainty of the HPR-assisted interpretation.Assessing this level of certainty may be helpful when making hydrocarbonmanagement decisions such as well placement, well design, platformplacement, reservoir management etc. FIGS. 8-12 demonstrate howHPR-assisted dataset interpretation can be combined with datauncertainty analysis to decide where to locate a well. FIG. 8 is agraphical display 70 of a dataset representing a subsurface region ofinterest as viewed from above. A viewer, wearing a brainwave-sensingdevice such as device 10 in FIG. 1, views the graphical display whilethe viewer's EEG signals are detected by device 10 and recorded. Signalssensed by device 10 may indicate the viewer is highly confident ofcertain portions of the dataset. These high-confidence areas may besuperimposed on the graphical display and are shown as gridded areas 72.The high-confidence areas may be further ranked, such as by contouring74, with the points of highest confidence being indicated by the letter“H”, for example. On the other hand, signals sensed by device 10 mayindicate the viewer is highly confused by certain other portions of thedataset. These high-confusion areas may be superimposed on the graphicaldisplay and are shown as stippled areas 76. The high-confusion areas maybe further ranked, such as by contouring 78, with the points of highestconfusion being indicated by the letter “H”, for example. Other mentalstates, such as thinking, stress, and others, may be sensed andsuperimposed on the graphical display.

The user may also be employing an eye-tracking mechanism as describedherein and shown in previous Figures. FIG. 9 shows areas of thegraphical display that were gazed on by the user, as sensed by theeye-tracking mechanism, with darker areas 82 indicating a longer gazeand lighter areas 84 indicating a shorter gaze.

The dataset displayed by graphical display 70 may have a measure ofuncertainty associated therewith. Such uncertainty may be due topotential errors in gathering the dataset, analyzing the dataset, orother events or acts that may affect the quality and/or uncertainty ofthe dataset. FIG. 10 depicts a single level of uncertainty superimposedon portions 90 of the graphical display 70 of the dataset, although manyuncertainty levels may be calculated and/or displayed if desired.

FIG. 11 shows how the results from HPR sensors (FIGS. 8 and 9) anduncertainty analysis (FIG. 10) may be superimposed simultaneously on thegraphical display of the dataset to create a more holistic or completerepresentation of how the viewer has analyzed the dataset. An additionalset of information about the dataset is shown in FIG. 12, in whichstructural contour lines 92 are superimposed on the graphical display.Arrows 93 point in directions of decreasing structural elevation. Allthe information superimposed on the graphical display may assist indeciding on potential site for a well. Three candidate sites, A, B, C,are shown in FIG. 12. Candidate site A is located at a high elevationpoint, but this location was marked as a highly confusing site by theuser (FIG. 8). Additionally, candidate site A was marked as a sitecharacterized by data uncertainty (FIG. 10). Candidate site B is locatedat a high elevation point, but this location was marked as a sitecharacterized by data uncertainty (FIG. 10). Furthermore, whilecandidate site B is not an area of high confusion or high confidence(FIG. 8), it was virtually ignored by the user (FIG. 9). Candidate siteC, on the other hand, is located in an area of high confidence (FIG. 8),and is not located in an area of data uncertainty (FIG. 10). Based onthe combined inputs as visually expressed in FIGS. 8-12, candidate siteC is the preferred well location.

In another aspect, it may be desired to examine a previousinterpretation or decision for quality control purposes or otherpurposes. If the interpretation/decision has HPR attributes associatedtherewith, the user may use the existing HPR responses to robustlyidentify and review regions and features that when initially interpretedhad anomalous QLOC measurements. In such a review mode these potentiallyanomalous features are presented automatically to the user, therebymaking the review of QLOC a guided process. The HPR measurements of thereviewing user may be added to the existing interpretation or decisionobject, thereby providing an additional set of information to thedataset. On the other hand, if the interpretation/decision does not haveHPR attributes associated therewith, the HPR attributes of the reviewinguser are sensed while evaluating the previous interpretation ordecision. The HPR attributes of the reviewing user are collected andassociated with the events and objects as they are reviewed. Inaddition, other information relating to editing/manipulation of theobject (such as time of review, duration of review, and the identity ofthe reviewing user) could be associated with the object to provideadditional information relating to the interpretation of the object.

In another aspect, it may be possible to evaluate certainty in recentlycollected data (or analogous predictions) associated with reservoirand/or well performance. Such data may include produced/injectedvolumes, well tests, production/profile logs, pressure measurements,and/or seismic data. While conducting this certainty evaluation, a useris wearing a device that senses brainwave activity or other humanphysiological responses. The physiological responses are then associatedwith the corresponding data (or analogous predictions) as new attributesindicating certainty. These attributes could then be queried andvisualized to make decisions at the field scale (such as collectingadditional data or conducting further analysis) and to share insightswith other team members, new staff, management, field personnel, etc.HPR measurements such as those measuring brainwave activity may betracked over time to evaluate individual performance or to determinebenefits from training, a user's ability to assimilate newresponsibilities, and to evaluate changes in certainty with changes inpractices used to collect data and/or generate predictions.

In another aspect, a human physiological response may be associated withdata or interpretation/decision objects. While a user is examining dataan HPR recording device may record HPR attributes such as brainwaveactivity, gaze, cursor position, rate of actuating an input device suchas a mouse, etc. The HPR attributes are associated with the raw data orinterpretation objects. The recorded attributes can be used to determinewhat data the user considered when reviewing the given dataset. Forexample, a hyrdocarbon asset such as a well or reservoir may beconsidered for abandonment. Reviewing the memory attributes associatedwith a dataset representing the hydrocarbon asset may aid in identifyingareas which weren't originally considered during the initialinterpretation/decision making process. This process could be furtherspecialized by identifying specific types of objects for which theattributes will be recorded.

FIG. 13 is a flowchart showing a method 100 according to aspects ofdisclosed methodologies and techniques. According to the method, atblock 101 a computer-based data interpretation or decision-making workflow is initiated. Example workflows include seismic interpretation,well planning, geologic interpretation, well design, history matching,reservoir surveillance, or other computer-based decision-making processrelated to hydrocarbon management. A user is wearing or accessing an HPRmonitoring device such as the headset of FIG. 1, the eye-trackingmechanism of FIG. 2, and/or a muscle-movement or mechanical eventtracking mechanism such as a computer mouse or trackball, or the like.At block 102 the monitoring of human physiological responses commenceswhile the user is reviewing the data or workflow. At block 103 humanphysiological responses are recorded, associated with the interpretationand/or analysis of data or workflow, and stored in the HPR managementsystem either in raw form or in a processed form. At block 104 the HPRdata is retrieved from the HPR management system and then processedseparately, in any combination with other human physiological responses,and/or with data uncertainties with the output. The processed data isthen stored in the HPR management system as a new attribute associatedwith the portion of the data or workflow that caused the humanphysiological responses. At block 105 the results of block 103 and/orblock 104 are displayed or otherwise visualized to better understand theQLOC. At block 106 the data interpretation/workflow is continued, takinginto account the results of block 103 and/or block 104. Thisvisualization may be on a display with or without the data or workflowwith which the processed HPR data is associated.

FIG. 14 is a flowchart showing a method 110 according to another aspectof the disclosed methodologies and techniques in which multiple usersare interpreting data or evaluating workflows using human physiologicalresponse technology. For the sake of brevity blocks in FIG. 14 similarto blocks in FIG. 13 are not fully described again, it being understoodthat the description of FIG. 13 applies to FIG. 14. At blocks 111 a . .. 111 n each user begins a computer-based data interpretation ordecision-making work flow. Such interpretation is not required to be atthe same time. The interpretations can be weighted equally or weightedaccording to relative experience or qualifications. The interpretationsmay be weighted by other factors as well. One interpretation can be acheck or review of another interpretation. At blocks 112 a . . . 112 nthe monitoring of human physiological responses events commences. Atblock 113 human physiological responses are recorded, associated withthe interpretation and/or analysis of data or workflow, and stored inthe HPR management system either in raw form or in a processed form. Atblock 114 the HPR data is retrieved from the HPR management system,processed, and stored in the HPR management system as a new attributeassociated with the portion of the data or workflow that caused thephysiological responses. At block 115 the results of block 113 and/orblock 114 are displayed or otherwise visualized to better understand theQLOC. At block 116 the data interpretation/workflow is continued, takinginto account the results of block 113 and/or block 114.

FIG. 15 is a flowchart showing a method 120 according to another aspectof the disclosed methodologies and techniques. Method 120 demonstrateshow HPR technologies may be used to evaluate previous datainterpretations/decisions or workflow results. At block 121 the analysistask is begun. At block 122 human physiological responses are monitored,as previously described with respect to blocks 102 and 112 of previouslydescribed aspects. At block 123 data relating to a previously madedecision is displayed and evaluated while HPR technologies are beingemployed. At block 124 data representing human physiological responsesis displayed or otherwise visualized with respect to thepreviously-analyzed data. This displaying of HPR data may beaccomplished by superimposing numeric or graphic elements representingthe HPR data (as shown in FIGS. 3 and 5-12, for example) onto thepreviously analyzed data. At block 125 physiological responses eventsare recorded, associated with the interpretation and/or analysis of dataor workflow, and stored in the HPR management system either in raw formor in a processed form. At block 126 the HPR data is retrieved from theHPR management system and then processed separately, in any combinationwith other physiological responses, and/or with data uncertainties withthe output. The processed data is then stored in the HPR managementsystem as a new attribute associated with the portion of the data orworkflow that caused the physiological responses. at block 127 theprocessed HPR data is then used to finalize a decision relating to theprevious data interpretation and/or workflow. Alternatively, theprocessed HPR data may be used to evaluate an initial decision madewithout integrating HPR data therewith.

The disclosure has provided various examples of computer systems orportions thereof, any of which may be used to provide an HPR monitoringsystem and/or an HPR processing system. A more complete illustration ofa system for implementing aspects of the disclosed methodologies andtechniques is depicted in FIG. 16, it being understood that aspectspreviously disclosed may be incorporated into part or all of the systemin FIG. 16. The system includes a computing device in the form of acomputing system 210, which may be a UNIX-based workstation or acommercially available system from Intel, IBM, AMD, Motorola, Cyrixand/or others. Components of the computing system 210 may include, butare not limited to, a processing unit 214, a system memory 216, and asystem bus 246 that couples various system components including thesystem memory to the processing unit 214. The system bus 246 may be anyof several types of bus structures including a memory bus or memorycontroller, a peripheral bus, and a local bus using any of a variety ofbus architectures.

Computing system 210 typically includes a variety of computer readablemedia. Computer readable media may be any available media that may beaccessed by the computing system 210 and includes both volatile andnonvolatile media, and removable and non-removable media. By way ofexample, and not limitation, computer readable media may comprisecomputer storage media and communication media. Computer storage mediaincludes volatile and nonvolatile, removable and non removable mediaimplemented in any method or technology for storage of information suchas computer readable instructions, data structures, program modules orother data.

Computer memory includes, but is not limited to, RAM, ROM, EEPROM, flashmemory or other memory technology, CD-ROM, digital versatile disks (DVD)or other optical disk storage, magnetic cassettes, magnetic tape,magnetic disk storage or other magnetic storage devices, or any othermedium which may be used to store the desired information and which maybe accessed by the computing system 210.

The system memory 216 includes computer storage media in the form ofvolatile and/or nonvolatile memory such as read only memory (ROM) 220and random access memory (RAM) 222. A basic input/output system 224(BIOS), containing the basic routines that help to transfer informationbetween elements within computing system 210, such as during start-up,is typically stored in ROM 220. RAM 222 typically contains data and/orprogram modules that are immediately accessible to and/or presentlybeing operated on by processing unit 214. By way of example, and notlimitation, FIG. 16 illustrates operating system 226, applicationprograms 230, other program modules 230 and program data 232.

Computing system 210 may also include other removable/non-removable,volatile/nonvolatile computer storage media. By way of example only,FIG. 16 illustrates a hard disk drive 234 that reads from or writes tonon-removable, nonvolatile magnetic media, a magnetic disk drive 236that reads from or writes to a removable, nonvolatile magnetic disk 238,and an optical disk drive 240 that reads from or writes to a removable,nonvolatile optical disk 242 such as a CD ROM or other optical media.Other removable/non-removable, volatile/nonvolatile computer storagemedia that may be used in the exemplary operating environment include,but are not limited to, magnetic tape cassettes, flash memory cards,digital versatile disks, digital video tape, solid state RAM, solidstate ROM, and the like. The hard disk drive 234 is typically connectedto the system bus 246 through a non-removable memory interface such asinterface 244, and magnetic disk drive 236 and optical disk drive 240are typically connected to the system bus 246 by a removable memoryinterface, such as interface 248.

The drives and their associated computer storage media, discussed aboveand illustrated in FIG. 16, provide storage of computer readableinstructions, data structures, program modules and other data for thecomputing system 210. In FIG. 16, for example, hard disk drive 234 isillustrated as storing operating system 278, application programs 280,other program modules 282 and program data 284. These components mayeither be the same as or different from operating system 226,application programs 230, other program modules 230, and program data232. Operating system 278, application programs 280, other programmodules 282, and program data 284 are given different numbers heretoillustrates that, at a minimum, they are different copies.

A user may enter commands and information into the computing system 210through input devices such as a tablet, or electronic digitizer, 250, amicrophone 252, a keyboard 254, and pointing device 256, commonlyreferred to as a mouse, trackball, or touch pad. These and other inputdevices often may be connected to the processing unit 214 through a userinput interface 258 that is coupled to the system bus 218, but may beconnected by other interface and bus structures, such as a parallelport, game port or a universal serial bus (USB). Other input devices mayinclude various devices that sense human physiological responses asdiscussed herein.

A monitor 260 or other type of display device may be also connected tothe system bus 218 via an interface, such as a video interface 262. Themonitor 260 may be integrated with a touch-screen panel or the like. Themonitor and/or touch screen panel may be physically coupled to a housingin which the computing system 210 is incorporated, such as in atablet-type personal computer. In addition, computers such as thecomputing system 210 may also include other peripheral output devicessuch as speakers 264 and printer 266, which may be connected through anoutput peripheral interface 268 or the like.

Computing system 210 may operate in a networked environment usinglogical connections to one or more remote computers, such as a remotecomputing system 270. The remote computing system 270 may be a personalcomputer, a server, a router, a network PC, a peer device or othercommon network node, and typically includes many or all of the elementsdescribed above relative to the computing system 210, although only amemory storage device 272 has been illustrated in FIG. 16. The logicalconnections depicted in FIG. 16 include a local area network (LAN) 274connecting through network interface 286 and a wide area network (WAN)276 connecting via modem 288, but may also include other networks. Suchnetworking environments are commonplace in offices, enterprise-widecomputer networks, intranets and the Internet.

For example, computer system 210 may comprise the source machine fromwhich data is being transferred, and the remote computing system 270 maycomprise the destination machine. Note however that source anddestination machines need not be connected by a network or any othermeans, but instead, data may be transferred via any machine-readablemedia capable of being written by the source platform and read by thedestination platform or platforms.

The central processor operating system or systems may reside at acentral location or distributed locations (i.e., mirrored orstand-alone). Software programs or modules instruct the operatingsystems to perform tasks such as, but not limited to, facilitatingclient requests, system maintenance, security, data storage, databackup, data mining, document/report generation and algorithms. Theprovided functionality may be embodied directly in hardware, in asoftware module executed by a processor or in any combination of thetwo.

Furthermore, software operations may be executed, in part or wholly, byone or more servers or a client's system, via hardware, software moduleor any combination of the two. A software module (program or executable)may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROMmemory, registers, hard disk, a removable disk, a CD-ROM, DVD, opticaldisk or any other form of storage medium known in the art. For example,a storage medium may be coupled to the processor such that the processormay read information from, and write information to, the storage medium.In the alternative, the storage medium may be integral to the processor.The processor and the storage medium may also reside in anapplication-specific integrated circuit (ASIC). The bus may be anoptical or conventional bus operating pursuant to various protocols thatare well known in the art. One system that may be used is a Linuxworkstation configuration with a Linux 64-bit or 32-bit Red Hat LinuxWS3 operating system, and an NVIDIA Quadro graphics card. However, thesystem may operate on a wide variety of hardware.

FIG. 17 is a block diagram of a representation of machine-readable code300 that may be used with a computing system such as computing system210. Reference may be made to previously described aspects to more fullyexplain each block in code 300. At block 302, code is provided forpresenting data representative of a workflow or a hydrocarbonmanagement-related activity. At block 304, code is provided for sensinga physiological response of a viewer of the data. At block 306, code isprovided for associating the physiological response with the data, andpreferably the portion of the data that caused the viewer to experienceor effectuate the observed physiological response. At block 308 the dataand its associated physiological response are outputted, for example toa display or to a storage device. Code effectuating or executing otherfeatures of the disclosed aspects and methodologies may be provided aswell. This additional code is represented in FIG. 17 as block 310, andmay be placed at any location within code 300 according to computer codeprogramming techniques.

Aspects disclosed herein may be used to conduct hydrocarbon managementactivities, such as extracting hydrocarbons from a subsurface region,which is indicated by reference number 320 in FIG. 18. A method 330 ofextracting hydrocarbons from subsurface reservoir 320 is shown in FIG.19. At block 332 HPR data is displayed or provided. The HPR data may besuperimposed on geologic or geophysical data as described and depictedherein. At block 334 the presence and/or location of hydrocarbons in thesubsurface region is predicted. At block 336 hydrocarbon extraction isconducted to remove hydrocarbons from the subsurface region, which maybe accomplished by drilling a well 334 using oil drilling equipment 336(FIG. 18). Other hydrocarbon management activities may be performedaccording to known principles.

The disclosed embodiments and methodologies may be susceptible tovarious modifications and alternative forms and have been shown only byway of example. The disclosed embodiments and methodologies are notintended to be limited to the particular embodiments disclosed herein,but include all alternatives, modifications, and equivalents fallingwithin the spirit and scope of the appended claims.

What is claimed is:
 1. A method of analyzing hydrocarbon-related data,comprising: displaying a graphical form of data representative of ahydrocarbon entity; sensing a physiological response of a viewer of thegraphical form of the data; associating the physiological response withthe graphical form of the data; and outputting the data and arepresentation of the associated physiological response, whereinassociating the physiological response with the graphical form of thedata comprises assigning measurements of the physiological response to asingle point or to a group of points of the graphical form of the datarepresentative for the hydrocarbon entity.
 2. The method of claim 1,wherein the representation of the associated physiological response isdisplayed in a graphical form.
 3. The method of claim 1, wherein therepresentation of the associated physiological response is superimposedupon the data.
 4. The method of claim 1, wherein the physiologicalresponse comprises at least one of brainwave activity, movement of aneye, position of an eye, gaze, muscle movement, body temperature, heartrate, pulmonary performance, and change in tone of voice.
 5. The methodof claim 1, wherein the physiological response comprises at least one ofa rate of use of an input device, and a position of an input devicerelative to the presented data representative of the hydrocarbon entity.6. The method of claim 1, wherein outputting the data and the associatedrepresentation of the physiological response comprises storing the dataand the representation in a memory.
 7. The method of claim 1, furthercomprising interpreting the physiological response based on informationregarding the viewer.
 8. The method of claim 1, wherein outputting thedata comprises storing the data in a raw form or a processed form. 9.The method of claim 1, wherein the viewer of the graphical form of thedata is a first viewer of the graphical form of the data, and furthercomprising: sensing a physiological response of a second viewer of thegraphical form of the data; associating the physiological response ofthe second viewer with the graphical form of the data; and outputtingthe data and a representation of the associated physiological responsesof the first and second viewers.
 10. An apparatus for analyzinghydrocarbon-related data, comprising: one or more sensors for measuringphysiological responses of a user viewing a graphical form of datarepresentative of a hydrocarbon entity; a processor that determines anature of the physiological response and associates the physiologicalresponse with a single point or a group of points of the graphical formof the data representative of the hydrocarbon entity; and an outputmechanism that stores information describing the physiological responsewith the data representative of a hydrocarbon entity responsible for thephysiological response.
 11. The apparatus of claim 10, furthercomprising a display for viewing the hydrocarbon-related data.
 12. Theapparatus of claim 10, wherein the one or more sensors includes a devicethat records brainwave activity of the user or an eye-tracking devicethat senses one or more of eye movement of the user, eye position of theuser, and gaze of the user.
 13. The apparatus of claim 12, furthercomprising a display for viewing the hydrocarbon-related data, whereinthe eye-tracking device is mounted on the display.
 14. The apparatus ofclaim 10, wherein the one or more sensors senses use of an input deviceas it is manipulated by the user, such as a computer mouse, a computertrackball, or a computer keyboard.
 15. A method of hydrocarbonmanagement, comprising: obtaining hydrocarbon-related information;analyzing the hydrocarbon-related information with the method accordingto any of the claims 1 to 9, thereby outputting a representation of aphysiological response of a viewer, associated to thehydrocarbon-related information, and managing hydrocarbons based on thephysiological response.
 16. The method of claim 15, wherein therepresentation of the physiological response is presented concurrentlywith a display of the hydrocarbon-related information.
 17. The method ofclaim 15, further comprising: obtaining certainty data related to thehydrocarbon-related information; presenting the certainty dataconcurrently with the representation of the physiological response andthe display of the hydrocarbon-related information; and managinghydrocarbons based on the certainty data and the physiological response.